Name UEMOTO Yoshinobu
Affiliation Associate Professor
Tel 022-757-4113
Fax 022-757-4117
Mail yoshinobu.uemoto.e7* replace * with @)
Research Interest Animal Breeding and Genetics, Quantitative Genetics
Career B.S. in Agriculture, Tohoku University; M.S. in Agriculture, Tohoku University. Experience: Ministry of Agriculture, Forestry and Fisheries (MAFF); National Livestock Breeding Center (NLBC); Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh; Tohoku University.
Research map
Research Projects

My research is to understand the genetic control of variation in quantitative traits and to apply the knowledge to livestock breeding by statistical methods. My research works are as follows:

1) Research on genetic improvement for quantitative traits such as meat production, meat quality, fertility, feed efficiency, and disease resistance in cattle and pigs.

2) Development of statistical methods to evaluate genetic abilities using genomic information.

3) Development of breeding strategies using new information obtained from next-generation sequencer (NGS) technology.

4) Search for DNA markers that can be useful for genetic selection by genome-wide association studies (GWAS).

Key words: BLUP, Genetic parameter, Genomic selection, GWAS, QTL, Quantitative genetics, SNP.

Research Seeds

Our scientific paper was selected for Animal Highlighted Article – November 2021

Recently, automatic feeders have become popular for collecting daily feed intake data, and day-to-day fluctuations in feed intake can be measured in pigs. Such longitudinal data could be regarded as an indicator of resilience. Resilience is the animal’s capacity to be minimally affected by disturbances or rapidly return to the state prevailing before exposure to a disturbance. The day-to-day fluctuations pattern can be expressed as changes in the overall performance of pigs under the assumption that pigs are constantly subject to unknown disturbance. Here, we estimated genetic parameters for resilience traits in three pig breeds, and our results show that resilience traits were heritable. This is a good example of how various information obtained through smart agriculture, such as automatic feeders, can be used for other perspectives as well.